NIRISSBackwardGrismDispersion

class stdatamodels.jwst.transforms.NIRISSBackwardGrismDispersion(orders, lmodels=None, xmodels=None, ymodels=None, theta=0.0)

Bases: _BackwardGrismDispersionBase

Calculate the dispersion extent of NIRISS pixels.

Initialize the model.

Parameters:

orderslist[int]

List of spectral orders corresponding to the dispersion models given by the lmodels, xmodels, and ymodels parameters.

lmodelslist[astropy.modeling.polynomial.Polynomial1D]

The inverse dispersion polynomial models, one per order, such that t = lmodel(wavelength) computes the wavelength from the trace parameter.

xmodelslist[list[astropy.modeling.polynomial.Polynomial2D]]

The models encoding the x-position of the spectral trace. Because the shape of the trace depends on the direct-image x0, y0 position, this takes the form dx = C0(x0, y0) + C1(x0, y0) * t + C2(x0, y0) * t^2. The inner list corresponds to the 2-D polynomials (C0, C1, C2). The outer list corresponds to the different spectral orders.

ymodelslist[list[astropy.modeling.polynomial.Polynomial2D]]

The models encoding the y-position of the spectral trace. Because the shape of the trace depends on the direct-image x0, y0 position, this takes the form dy = C0(x0, y0) + C1(x0, y0) * t + C2(x0, y0) * t^2. The inner list corresponds to the 2-D polynomials (C0, C1, C2). The outer list corresponds to the different spectral orders.

thetafloat

Angle [deg] - defines the NIRISS filter wheel position

Methods Summary

evaluate(x, y, wavelength, order)

Transform from the direct image plane to the dispersed plane.

Methods Documentation

evaluate(x, y, wavelength, order)

Transform from the direct image plane to the dispersed plane.

Parameters:

x, yfloat or np.ndarray

Input x, y location

wavelengthfloat or np.ndarray

Wavelength in angstroms

orderint

Input spectral order

Returns:

x, yfloat or np.ndarray

The x, y values in the dispersed plane.

x0, y0float or np.ndarray

Source object x-center, y-center. Same as input x, y.

orderint

Output spectral order, same as input

Notes

There’s spatial dependence for NIRISS so the forward transform depends on x,y as well as the filter wheel rotation. Theta is usu. taken to be the different between fwcpos_ref in the specwcs reference file and fwcpos from the input image.